# ModTrans: Translating Real-world Models for Distributed Training Simulator

arXiv: https://arxiv.org/abs/2604.01607 · HTML: https://mlsanity.com/paper/2604.01607/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in World models for language agents, one of 11 directions in World models.
- Builds on 8 of its 14 references that are in the map.
- First posted on arXiv 2 Apr 2026.

## Placed in

- World models / [World models for language agents](https://mlsanity.com/wm/world-models-for-language-agents/)

## Builds on (most cited first, 8 of 8)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://mlsanity.com/paper/1409.1556/) (2014)
- [PaLM: Scaling Language Modeling with Pathways](https://mlsanity.com/paper/2204.02311/) (2022)
- [Efflex: Efficient and Flexible Pipeline for Spatio-Temporal Trajectory Graph Modeling and Representation Learning](https://mlsanity.com/paper/2404.12400/) (2024)
- [VeTraSS: Vehicle Trajectory Similarity Search Through Graph Modeling and Representation Learning](https://mlsanity.com/paper/2404.08021/) (2024)
- [CATP: Cross-Attention Token Pruning for Accuracy Preserved Multimodal Model Inference](https://mlsanity.com/paper/2404.08567/) (2024)
- [MonoM: Enhancing Monotonicity in Learned Cardinality Estimators](https://mlsanity.com/paper/2512.22122/) (2025)
- [Safeguard: Security Controls at the Software Defined Network Layer](https://mlsanity.com/paper/2601.17355/) (2026)

## Abstract (arXiv)

Large-scale distributed training has been a research hot spot in machine learning systems for industry and academia in recent years. However, conducting experiments without physical machines and corresponding resources is difficult. One solution is to leverage distributed training simulators, but current ones like ASTRA-sim do not support importing real-world developed models, which poses challenges for ML researchers seeking to use them. Based on this challenge, we developed ModTrans, a translator supporting format translation from any real-world model to the ASTRA-sim simulator's input, removing the barrier between machine learning experts and machine learning system researchers. The experiment results show that ModTrans's cost is negligible.